Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the majority of the experimental maps in the database lack atomic resolution features, making it challenging for machine learning-based methods to precisely determine protein structures from cryogenic electron microscopy density maps. On the other hand, protein structure prediction methods, such as AlphaFold2, leverage evolutionary information from protein sequences and have recently achieved groundbreaking accuracy. However, these methods often require manual refinement, which is labor intensive and time consuming. In this study, we present DeepTracer-Refine, an automated method that refines AlphaFold predicted structures by aligning them to DeepTracers modeled structure. Our method was evaluated on 39 multi-domain proteins and we improved the average residue coverage from 78.2 to 90.0% and average local Distance Difference Test score from 0.67 to 0.71. We also compared DeepTracer-Refine with Phenixs AlphaFold refinement and demonstrated that our method not only performs better when the initial AlphaFold model is less precise but also surpasses Phenix in run-time performance.

Cenozoic Indo-Pacific warm pool controlled by both atmospheric CO2 and paleogeography.

The Indo-Pacific warm pool (IPWP) is crucial for regional and global climates. However, the development of the IPWP and its effect on the regional climate during the Cenozoic remain unclear. Here, using a compilation of sea surface temperature (SST) records (mainly since the middle Miocene) and multimodel paleoclimate simulations, our results indicated that the extent, intensity and warmest temperature position of the IPWP changed markedly during the Cenozoic. Specifically, its extent decreased, its intensity weakened, and its warmest temperature position shifted from the Indian to western Pacific Ocean over time. The atmospheric CO2 dominated its extent and intensity, while paleogeography, by restricting the distribution of the Indian Ocean and the width of the tropical seaways, controlled the shift in its warmest temperature position. In particular, the eastward shift to the western Pacific Ocean from the middle to late Miocene inferred from compiled SST records likely resulted from the constriction of tropical seaways. Furthermore, by changing the atmospheric thermal structure and atmospheric circulation, the reduced extent and intensity of the IPWP decreased the annual precipitation in the western Indian Ocean, eastern Asia and Australia, while the shift in the warmest temperature position from the Indian to western Pacific Ocean promoted aridification in Australia. Qualitative model-data agreements are obtained for both the IPWP SST and regional climate. From the perspective of past warm climates with high concentrations of atmospheric CO2, the expansion and strengthening of the IPWP will occur in a warmer future and favor excessive precipitation in eastern Asia and Australia.

ComplexQA: a deep graph learning approach for protein complex structure assessment.

MOTIVATION: In recent years, the end-to-end deep learning method for single-chain protein structure prediction has achieved high accuracy. For example, the state-of-the-art method AlphaFold, developed by Google, has largely increased the accuracy of protein structure predictions to near experimental accuracy in some of the cases. At the same time, there are few methods that can evaluate the quality of protein complexes at the residue level. In particular, evaluating the quality of residues at the interface of protein complexes can lead to a wide range of applications, such as protein function analysis and drug design. In this paper, we introduce a new deep graph neural network-based method ComplexQA, to evaluate the local quality of interfaces for protein complexes by utilizing the residue-level structural information in 3D space and the sequence-level constraints. RESULTS: We benchmark our method to other state-of-the-art quality assessment approaches on the HAF2 and DBM55-AF2 datasets (high-quality structural models predicted by AlphaFold-Multimer), and the BM5 docking dataset. The experimental results show that our proposed method achieves better or similar performance compared with other state-of-the-art methods, especially on difficult targets which only contain a few acceptable models. Our method is able to suggest a score for each interfac e residue, which demonstrates a powerful assessment tool for the ever-increasing number of protein complexes. AVAILABILITY: https://github.com/Cao-Labs/ComplexQA.git. Contact: caora@plu.edu.

Efficacy and safety of telitacicept in patients with systemic lupus erythematosus: a multicentre, retrospective, real-world study.

OBJECTIVE: To examine the efficacy and safety of telitacicept in the treatment of patients with SLE in everyday clinical practice. METHODS: Seventy-two patients with active SLE who received telitacicept for more than 24 weeks at multiple centres in China between 2019 and 2022 were retrospectively identified. Twenty-one of these patients received 52 continuous weeks of treatment with telitacicept. Treatment outcomes were analysed separately according to whether patients had renal or haematological abnormalities. Trajectory analysis was performed to identify patients with a limited response. Factors contributing to a limited response were explored by multivariable logistic regression analysis. RESULTS: After treatment with telitacicept for 4, 12, 24 and 52 weeks, 22.22%, 54.17%, 72.22% and 80.95% of patients, respectively, achieved an SLE Responder Index 4; 8.33%, 26.39%, 34.72% and 47.62% achieved a Lupus Low Disease Activity State; and 0%, 4.17%, 8.33% and 23.81% achieved remission. Significant decreases in serum IgA, IgG and IgM levels were observed at 4 weeks and showed a downward trend at 12, 24 and 52 weeks. The median 24-hour urinary protein declined from 1323.5 mg to 224.0 mg in patients with lupus nephritis after treatment with telitacicept for 52 weeks. Furthermore, a large proportion of patients (10 of 13) with haematological abnormalities recovered after 52 weeks of treatment with telitacicept. No severe adverse events were reported during the observation period. Age appeared to have a negative impact on treatment efficacy. CONCLUSIONS: Telitacicept demonstrated favourable efficacy and safety in patients with active SLE and improved the renal and haematological manifestations of the disease.

Single-cell characterization of self-renewing primary trophoblast organoids as modeling of EVT differentiation and interactions with decidual natural killer cells.

BACKGROUND: Extravillous trophoblast cell (EVT) differentiation and its communication with maternal decidua especially the leading immune cell type natural killer (NK) cell are critical events for placentation. However, appropriate in vitro modelling system and regulatory programs of these two events are still lacking. Recent trophoblast organoid (TO) has advanced the molecular and mechanistic research in placentation. Here, we firstly generated the self-renewing TO from human placental villous and differentiated it into EVTs (EVT-TO) for investigating the differentiation events. We then co-cultured EVT-TO with freshly isolated decidual NKs for further study of cell communication. TO modelling of EVT differentiation as well as EVT interaction with dNK might cast new aspect for placentation research. RESULTS: Single-cell RNA sequencing (scRNA-seq) was applied for comprehensive characterization and molecular exploration of TOs modelling of EVT differentiation and interaction with dNKs. Multiple distinct trophoblast states and dNK subpopulations were identified, representing CTB, STB, EVT, dNK1/2/3 and dNKp. Lineage trajectory and Seurat mapping analysis identified the close resemblance of TO and EVT-TO with the human placenta characteristic. Transcription factors regulatory network analysis revealed the cell-type specific essential TFs for controlling EVT differentiation. CellphoneDB analysis predicted the ligand-receptor complexes in dNK-EVT-TO co-cultures, which relate to cytokines, immunomodulation and angiogenesis. EVT was known to affect the immune properties of dNK. Our study found out that on the other way around, dNKs could exert effects on EVT causing expression changes which are functionally important. CONCLUSION: Our study documented a single-cell atlas for TO and its applications on EVT differentiation and communications with dNKs, and thus provide methodology and novel research cues for future study of human placentation.

JMJD6 protects against isoproterenol-induced cardiac hypertrophy via inhibition of NF-κB activation by demethylating R149 of the p65 subunit.

Histone modification plays an important role in pathological cardiac hypertrophy and heart failure. In this study we investigated the role of a histone arginine demethylase, Jumonji C domain-containing protein 6 (JMJD6) in pathological cardiac hypertrophy. Cardiac hypertrophy was induced in rats by subcutaneous injection of isoproterenol (ISO, 1.2 mg·kg-1·d-1) for a week. At the end of the experiment, the rats underwent echocardiography, followed by euthanasia and heart collection. We found that JMJD6 levels were compensatorily increased in ISO-induced hypertrophic cardiac tissues, but reduced in patients with heart failure with reduced ejection fraction (HFrEF). Furthermore, we demonstrated that JMJD6 overexpression significantly attenuated ISO-induced hypertrophy in neonatal rat cardiomyocytes (NRCMs) evidenced by the decreased cardiomyocyte surface area and hypertrophic genes expression. Cardiac-specific JMJD6 overexpression in rats protected the hearts against ISO-induced cardiac hypertrophy and fibrosis, and rescued cardiac function. Conversely, depletion of JMJD6 by single-guide RNA (sgRNA) exacerbated ISO-induced hypertrophic responses in NRCMs. We revealed that JMJD6 interacted with NF-κB p65 in cytoplasm and reduced nuclear levels of p65 under hypertrophic stimulation in vivo and in vitro. Mechanistically, JMJD6 bound to p65 and demethylated p65 at the R149 residue to inhibit the nuclear translocation of p65, thus inactivating NF-κB signaling and protecting against pathological cardiac hypertrophy. In addition, we found that JMJD6 demethylated histone H3R8, which might be a new histone substrate of JMJD6. These results suggest that JMJD6 may be a potential target for therapeutic interventions in cardiac hypertrophy and heart failure.

Discovery of ZFD-10 of a pyridazino[4,5-b]indol-4(5H)-one derivative as an anti-ZIKV agent and a ZIKV NS5 RdRp inhibitor.

Zika virus (ZIKV) infection is associated with the birth defect microcephaly and Guillain-Barré syndrome in adults. There is no approved vaccine or specific antiviral agent against ZIKV. ZFD-10, a novel structural skeleton of 1H-pyridazino[4,5-b]indol-4(5H)-one, was firstly synthesized and discovered to be a potent anti-ZIKV inhibitor with very low cytotoxicity. ZFD-10's anti-ZIKV potency is independent of cell lines and ZFD-10 mainly targets the post-entry stages of ZIKV life cycle. Time-of-addition and time-of-withdrawal assays showed that 10 µM ZFD-10 displayed the ability to decrease mainly at the RNA level and weakly the viral progeny particle load. Furthermore, ZFD-10 could protect ZIKV NS5 from thermal unfolding and aggregation and increase the Tagg value of ZIKV NS5 protein from 44.6 to 49.3 °C, while ZFD-10 dose-dependently inhibits ZIKV NS5 RdRp activity using in vitro RNA polymerase assays. Molecular docking study suggests that ZFD-10 affects RdRp enzymatic function through interfering with the fingers and thumb subdomains. These results supported that ZFD-10's cell-based anti-ZIKV activity is related to its anti-RdRp activity of ZIKV NS5. The in vivo anti-ZIKV study shows that the middle-dose (4.77 mg/kg/d) of ZFD-10 protected mice from ZIKV infection and the viral loads of the blood, liver, kidney and brain in the middle-dose and high-dose (9.54 mg/kg/d) were significantly reduced compared to those of the ZIKV control. These results confirm that ZFD-10 has a certain antiviral effect against ZIKV infection in vivo.

Integrated Surface Modulation of Ultrahigh Ni Cathode Materials for Improved Battery Performance.

Ni-rich layered cathodes with ultrahigh nickel content (≥90%), for example LiNi0.9 Co0.1 O2 (NC0.9), are promising for next-generation high-energy Li-ion batteries (LIBs), but face stability issues related to structural degradation and side reactions during the electrochemical process. Here, surface modulation is demonstrated by integrating a Li+ -conductive nanocoating and gradient lattice doping to stabilize the active cathode efficiently for extended cycles. Briefly, a wet-chemistry process is developed to deposit uniform ZrO(OH)2 nanoshells around Ni0.905 Co0.095 (OH)2 (NC0.9-OH) hydroxide precursors, followed by high temperature lithiation to create reinforced products featuring Zr doping in the crust lattice decorated with Li2 ZrO3 nanoparticles on the surface. It is identified that the Zr4+ infiltration reconstructed the surface lattice into favorable characters such as Li+ deficiency and Ni3+ reduction, which are effective to combat side reactions and suppress phase degradation and crack formation. This surface control is able to achieve an optimized balance between surface stabilization and charge transfer, resulting in an extraordinary capacity retention of 96.6% after 100 cycles at 1 C and an excellent rate capability of 148.8 mA h g-1 at 10 C. This study highlights the critical importance of integrated surface modulation for high stability of cathode materials in next-generation LIBs.

Structure-based discovery of novel α-aminoketone derivatives as dual p53-MDM2/MDMX inhibitors for the treatment of cancer.

The function of the p53 protein is impaired by the overexpression of its negative regulator murine double minute 2 protein (MDM2) and homologous protein MDMX. Disruption of the p53-MDM2/MDMX interaction to restore the transcriptional function of p53 is considered a promising strategy for cancer therapy. To design dual MDM2/MDMX inhibitors, the binding modes of MDM2 or MDMX with their inhibitors are elucidated. Several hot-spot residues of MDM2 or MDMX are identified by molecular dynamics simulations, alanine scanning and MM-GBSA calculations. Then, focusing on the interaction with hot-spot residues, two series of derivatives bearing 1,3-diketone and α-aminoketone scaffolds are designed and synthesized. Among these compounds, C16 is identified as the most potent compound with low micromolar binding affinities with MDM2 and MDMX. C16 also displays moderate antiproliferative activities against MDM2-overexpressing and MDMX-overexpressing cells, with IC50 values of 0.68 µM in HCT116 cells and 0.54 µM in SH-SY5Y cells. Furthermore, C16 inhibits cell migration and invasion, reactivates the function of p53, arrests the cell cycle and induces cellular apoptosis in HCT116 and SH-SY5Y cells. Collectively, C16 can be developed as a dual MDM2 and MDMX inhibitor for cancer therapy.

Surface Lattice Modulation through Chemical Delithiation toward a Stable Nickel-Rich Layered Oxide Cathode.

Nickel-rich layered oxides (NLOs) are considered as one of the most promising cathode materials for next-generation high-energy lithium-ion batteries (LIBs), yet their practical applications are currently challenged by the unsatisfactory cyclability and reliability owing to their inherent interfacial and structural instability. Herein, we demonstrate an approach to reverse the unstable nature of NLOs through surface solid reaction, by which the reconstructed surface lattice turns stable and robust against both side reactions and chemophysical breakdown, resulting in improved cycling performance. Specifically, conformal La(OH)3 nanoshells are built with their thicknesses controlled at nanometer accuracy, which act as a Li+ capturer and induce controlled reaction with the NLO surface lattices, thereby transforming the particle crust into an epitaxial layer with localized Ni/Li disordering, where lithium deficiency and nickel stabilization are both achieved by transforming oxidative Ni3+ into stable Ni2+. An optimized balance between surface stabilization and charge transfer is demonstrated by a representative NLO material, namely, LiNi0.83Co0.07Mn0.1O2, whose surface engineering leads to a highly improved capacity retention and excellent rate capability with a strong capability to inhibit the crack of NLO particles. Our study highlights the importance of surface chemistry in determining chemical and structural behaviors and paves a research avenue in controlling the surface lattice for the stabilization of NLOs toward reliable high-energy LIBs.

Antiviral effects of the fused tricyclic derivatives of indoline and imidazolidinone on ZIKV infection and RdRp activities of ZIKV and DENV.

The prevalence and ravages of Zika virus (ZIKV) seriously endanger human health, especially causing significant neurological defects in both neonates as pediatric microcephaly and adults as Guillain-Barré syndrome. In this work, we studied anti-ZIKV effects of the fused tricyclic derivatives of indoline and imidazolidinone and discovered that some of them are valuable leads for drug discovery of anti-ZIKV agents. The current results show that certain compounds are broad-spectrum inhibitors of ZIKV- and dengue virus (DENV)-infection while distinctive compounds are selective ZIKV inhibitors or selective DENV inhibitors. Compounds of 12, 17 and 28 are more active against Asian ZIKV SZ-VIV01 strain than African ZIKV MR766 strain. It is valued that silylation makes six TBS compounds of 4-nitrophenyl hydrazine series and phenyl hydrazine series more active against ZIKV infection than their phenols. Time-of-addition and withdrawal studies indicate that compound 12 majorly acts on post-infection of RNA synthesis stage of ZIKV life cycle. Moreover, compounds of 12, 17 and 18 are anti-ZIKV agents with the inhibitory activities to ZIKV NS5 RdRp while 12 doesn't inhibit DENV infection even though it is a DENV RdRp inhibitor, 17 is an active agent against DENV infection but is only a weak DENV NS5 RdRp inhibitor, and 28 is inactive against DENV infection and not a DENV NS5 RdRp inhibitor. As a result, a compound's antiviral difference between ZIKV and DENV is not always related to anti-RdRp difference between ZIKV RdRp and DENV RdRp, and structural features of a compound play important roles in executing antiviral and anti-RdRp functions. Further discovery of highly potent broad-spectrum or selective agents against infection by ZIKV and DENV will be facilitated.

Two-dimensional shear wave elastography utilized in patients with ascites: a more reliable method than transient elastography for noninvasively detecting the liver stiffness-an original study with 170 patients.

Background: Two dimensional shear wave elastography (2D-SWE) is an ultrasound elastography technique based on shear waves implemented on a diagnostic ultrasound system. Transient elastography (TE) uses an ultrasound displacement M-mode and A-mode image produced by the system. So, TE mechanically induced impulse at tissue surface and difficultly across water. This paper compared the reliability and reproducibility of 2D-SWE with that of TE in patients with chronic hepatic disease. Comparisons were made in terms of the success rate, reliability, reproducibility, operation time, and influence of operator experience. Methods: A total of 170 patients were included in this study. Participants underwent 2D-SWE and TE performed by 2 different operators (a novice and veteran) on the same day. Nonparametric statistical tests were used to compare the technical success rate and reliable measurement rate, and inter-operator reproducibility was evaluated using intra-class correlation coefficients (ICCs). Results: The 2D-SWE technique showed a higher technical success rate than TE. Either 2D-SWE or TE can be utilized in patients with ascites lamella of less than 10 mm or ascites lamella plus skin-capsular distance of less than 25 mm. However, although the reliability rate of liver stiffness measurement with 2D-SWE did not significantly differ between the novice and veteran operators, for TE, there was a significant difference when body mass index (BMI) ≤25 kg/m2. When performed by the novice and veteran operators, 2D-SWE and TE both showed excellent inter-operator agreement, with ICCs of 0.968 and 0.973, respectively. Both 2D-SWE and TE displayed reliable measurement and excellent reproducibility in patients with chronic liver disease, were minimally influenced by operator experience. Conclusions: 2D-SWE may be a more reliable method for clinical application in noninvasive detecting the liver stiffness.

Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps.

Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model building of large macromolecular complexes is often difficult and time-consuming. We recently developed DeepTracer-2.0, an artificial-intelligence-based pipeline that can build amino acid and nucleic acid backbones from a single cryo-EM map, and even predict the best-fitting residues according to the density of side chains. The experiments showed improved accuracy and efficiency when benchmarking the performance on independent experimental maps of protein-DNA/RNA complexes and demonstrated the promising future of macromolecular modeling from cryo-EM maps. Our method and pipeline could benefit researchers worldwide who work in molecular biomedicine and drug discovery, and substantially increase the throughput of the cryo-EM model building. The pipeline has been integrated into the web portal https://deeptracer.uw.edu/.

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps.

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has increasingly become more popular due to recent advancements in hardware and software. The number of cryo-EM maps deposited in the EMDataResource (formerly EMDatabase) since 2002 has been dramatically increasing and it continues to do so. De novo macromolecular complex modeling is a labor-intensive process, therefore, it is highly desirable to develop software that can automate this process. Here we discuss our automated, data-driven, and artificial intelligence approaches including map processing, feature extraction, modeling building, and target identification. Recently, we have enabled DNA/RNA modeling in our deep learning-based prediction tool, DeepTracer. We have also developed DeepTracer-ID, a tool that can identify proteins solely based on the cryo-EM map. In this paper, we will present our accumulated experiences in developing deep learning-based methods surrounding macromolecule modeling applications.

Superiorization-inspired unrolled SART algorithm with U-Net generated perturbations for sparse-view and limited-angle CT reconstruction.

Objective.Unrolled algorithms are a promising approach for reconstruction of CT images in challenging scenarios, such as low-dose, sparse-view and limited-angle imaging. In an unrolled algorithm, a fixed number of iterations of a reconstruction method are unrolled into multiple layers of a neural network, and interspersed with trainable layers. The entire network is then trained end-to-end in a supervised fashion, to learn an appropriate regularizer from training data. In this paper we propose a novel unrolled algorithm, and compare its performance with several other approaches on sparse-view and limited-angle CT.Approach.The proposed algorithm is inspired by the superiorization methodology, an optimization heuristic in which iterates of a feasibility-seeking method are perturbed between iterations, typically using descent directions of a model-based penalty function. Our algorithm instead uses a modified U-net architecture to introduce the perturbations, allowing a network to learn beneficial perturbations to the image at various stages of the reconstruction, based on the training data.Main Results.In several numerical experiments modeling sparse-view and limited angle CT scenarios, the algorithm provides excellent results. In particular, it outperforms several competing unrolled methods in limited-angle scenarios, while providing comparable or better performance on sparse-view scenarios.Significance.This work represents a first step towards exploiting the power of deep learning within the superiorization methodology. Additionally, it studies the effect of network architecture on the performance of unrolled methods, as well as the effectiveness of the unrolled approach on both limited-angle CT, where previous studies have primarily focused on the sparse-view and low-dose cases.

Neural representations of cryo-EM maps and a graph-based interpretation.

BACKGROUND: Advances in imagery at atomic and near-atomic resolution, such as cryogenic electron microscopy (cryo-EM), have led to an influx of high resolution images of proteins and other macromolecular structures to data banks worldwide. Producing a protein structure from the discrete voxel grid data of cryo-EM maps involves interpolation into the continuous spatial domain. We present a novel data format called the neural cryo-EM map, which is formed from a set of neural networks that accurately parameterize cryo-EM maps and provide native, spatially continuous data for density and gradient. As a case study of this data format, we create graph-based interpretations of high resolution experimental cryo-EM maps. RESULTS: Normalized cryo-EM map values interpolated using the non-linear neural cryo-EM format are more accurate, consistently scoring less than 0.01 mean absolute error, than a conventional tri-linear interpolation, which scores up to 0.12 mean absolute error. Our graph-based interpretations of 115 experimental cryo-EM maps from 1.15 to 4.0 Å resolution provide high coverage of the underlying amino acid residue locations, while accuracy of nodes is correlated with resolution. The nodes of graphs created from atomic resolution maps (higher than 1.6 Å) provide greater than 99% residue coverage as well as 85% full atomic coverage with a mean of 0.19 Å root mean squared deviation. Other graphs have a mean 84% residue coverage with less specificity of the nodes due to experimental noise and differences of density context at lower resolutions. CONCLUSIONS: The fully continuous and differentiable nature of the neural cryo-EM map enables the adaptation of the voxel data to alternative data formats, such as a graph that characterizes the atomic locations of the underlying protein or macromolecular structure. Graphs created from atomic resolution maps are superior in finding atom locations and may serve as input to predictive residue classification and structure segmentation methods. This work may be generalized to transform any 3D grid-based data format into non-linear, continuous, and differentiable format for downstream geometric deep learning applications.

Structure of Geobacter OmcZ filaments suggests extracellular cytochrome polymers evolved independently multiple times.

While early genetic and low-resolution structural observations suggested that extracellular conductive filaments on metal-reducing organisms such as Geobacter were composed of type IV pili, it has now been established that bacterial c-type cytochromes can polymerize to form extracellular filaments capable of long-range electron transport. Atomic structures exist for two such cytochrome filaments, formed from the hexaheme cytochrome OmcS and the tetraheme cytochrome OmcE. Due to the highly conserved heme packing within the central OmcS and OmcE cores, and shared pattern of heme coordination between subunits, it has been suggested that these polymers have a common origin. We have now used cryo-electron microscopy (cryo-EM) to determine the structure of a third extracellular filament, formed from the Geobacter sulfurreducens octaheme cytochrome, OmcZ. In contrast to the linear heme chains in OmcS and OmcE from the same organism, the packing of hemes, heme:heme angles, and between-subunit heme coordination is quite different in OmcZ. A branched heme arrangement within OmcZ leads to a highly surface exposed heme in every subunit, which may account for the formation of conductive biofilm networks, and explain the higher measured conductivity of OmcZ filaments. This new structural evidence suggests that conductive cytochrome polymers arose independently on more than one occasion from different ancestral multiheme proteins.

Discovery of dehydroandrographolide derivatives with C19 hindered ether as potent anti-ZIKV agents with inhibitory activities to MTase of ZIKV NS5.

Infection by Zika virus (ZIKV), a mosquito-transmitted arbovirus and a member of Flavivirus, could make pediatric microcephaly and Guillain-Barré syndrome, which remains an ongoing global threat. The efficient antivirals to ZIKV infection are of great medical need. Andrographolide and its analogues were discovered to be active against flaviviral infection. In this study, we discovered some dehydroandrographolide derivatives of 3-oximido- or 3-alcohol-19-hindered ether to be potent anti-ZIKV agents with low cytotoxicities (CC50 > 200 µM). Time of addition assay suggests that compound 5a and its analogues act on inhibition of post-entry stage of ZIKV life cycle. It is discovered by experimental and molecular docking studies that active anti-ZIKV compounds of 3a, 5a, 5b and 5c possess inhibitory activities of ZIKV NS5 MTase (methyl transferase) enzymatic activity. Preliminary SAR reveals that C19-modification with bulky groups is necessary for anti-ZIKV infection and replication, anti-ZIKV activity of 5a comes from itself bearing hindered trityl ether but not from its instability, the backbone of dehydroandrographolide is more effective against ZIKV infection than that of andrographolide, and 3-oxime derivatives are more active against ZIKV infection than 3-alcohol derivatives. To our knowledge, 5a is the first reported MTase inhibitor of andrographolide derivatives. More importantly, discovery of active compound 5b with acid-stable 19-OCHPh2 against ZIKV infection is valued and gives us a clue to design and discover generally acid-stable anti-ZIKV agents.

Multi-omics characterization of the unsaturated fatty acid biosynthesis pathway in colon cancer.

The biosynthesis of unsaturated fatty acids is involved in the initiation and progression of colon adenocarcinoma (COAD). In this study, we aimed to investigate the multi-omics characteristics of unsaturated fatty acid biosynthesis-related genes and explore their prognostic value in colon cancer by analyzing the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. An unsaturated fatty acid biosynthesis pathway related-genes enrichment score (BUFAS) was constructed utilizing the single sample gene set enrichment analysis (ssGSEA). We discovered that a high BUFAS was associated with longer overall survival (OS) in both the training and the validation sets. Multivariable analysis including the clinical characteristics further verified the independent prognostic value of the BUFAS in both the TCGA-COAD and the GSE39582 datasets. In addition, GSEA analysis revealed that BUFAS was positively associated with several signaling pathways, including MTORC1, peroxisome, and pathways related to fatty acid metabolism, while was negatively associated with other signaling pathways, such as hedgehog, NOTCH, and Wnt/beta-catenin pathway. Furthermore, in the COAD cell lines of the Genomics of Drug Sensitivity in Cancer (GDSC) database, we found that BUFAS was positively correlated with the drug sensitivities of cisplatin, gemcitabine, camptothecin, lapatinib, and afatinib, while was negatively correlated with that of ponatinib. Moreover, in the COAD single-cell transcriptomic dataset (GSE146771), the BUFAS varied among different cell types and was enriched in mast cells and fibroblasts. Taken together, the BUFAS we constructed could be used as an independent prognostic signature in predicting the OS and drug resistance of colon cancer. Unsaturated fatty acid biosynthesis pathway might serve as potential therapeutic targets for cancer treatment.

Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space.

Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.